In order to evaluate the risk in the process of natural driving

Bayesian network was used to carry out quantitative research on driving risk. First

natural driving test was conducted to obtain the vehicle control data of vehicle spacing

acceleration

and steering entropy

as well as the eye movement data

including the driver’s sight transfer time

saccade speed

and blink frequency. Then

the risk rule of each index data was analyzed

and the risk level threshold of each index was determined. Finally

a vehicle operation risk assessment model based on Bayesian network was constructed

and the risk quantification classification method was proposed. The risk level of vehicle operation was determined

and the sensitivity of the model was analyzed. Results show that the Bayesian network model based on vehicle control and eye movement characterization could effectively conduct quantitative evaluation of driving risk in the driving process. The research results can provide theoretical and technical support for driving risk assessment and early warning in the natural driving process.